• Title/Summary/Keyword: IT support

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Academic Stress, Interpersonal Relationships, and College Life Adaptation of Nursing Students Who Experienced COVID-19 (코로나19를 경험한 간호대학생의 학업 스트레스, 대인관계 및 대학생활적응)

  • Eun-Young Kim
    • Journal of the Korean Applied Science and Technology
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    • v.39 no.6
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    • pp.783-791
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    • 2022
  • This Research is a descriptive study conducted to identify the academic stress, interpersonal relationships, and degree of adaptation to college life of nursing students who experienced COVID-19, and to identify factors influencing college life adaptation. The subjects of the research were sophomore students enrolled in 3 university nursing departments in G city. For data analysis, descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis were analyzed. The research result showed a significant negative correlation (r=-.584, p<.001) for academic stress and college life adaptation, and a significant positive correlation (r=.505, p<.001) for interpersonal relationships and college life adaptation. The regression model to confirm the influencing factors on college life adaptation was shown to be significant (F=64.462 p<.001). Academic stress (β=-.542, p<.001), interpersonal relationships (β=.339, p<.001), and housing type (β=.199, p<.001) were found to be significant predictive factors. The explanatory power of these variables was 54.6%. Through the results of this research, it will be possible to provide basic data for developing educational programs to reduce academic stress, improve positive and smooth interpersonal relationships, and improve emotional support for college life adaptation.

A Model for Supporting Information Security Investment Decision-Making Considering the Efficacy of Countermeasures (정보보호 대책의 효과성을 고려한 정보보호 투자 의사결정 지원 모형)

  • Byeongjo Park;Tae-Sung Kim
    • Information Systems Review
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    • v.25 no.4
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    • pp.27-45
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    • 2023
  • The importance of information security has grown alongside the development of information and communication technology. However, companies struggle to select suitable countermeasures within their limited budgets. Sönmez and Kılıç (2021) proposed a model using AHP and mixed integer programming to determine the optimal investment combination for mitigating information security breaches. However, their model had limitations: 1) a lack of objective measurement for countermeasure efficacy against security threats, 2) unrealistic scenarios where risk reduction surpassed pre-investment levels, and 3) cost duplication when using a single countermeasure for multiple threats. This paper enhances the model by objectively quantifying countermeasure efficacy using the beta probability distribution. It also resolves unrealistic scenarios and the issue of duplicating investments for a single countermeasure. An empirical analysis was conducted on domestic SMEs to determine investment budgets and risk levels. The improved model outperformed Sönmez and Kılıç's (2021) optimization model. By employing the proposed effectiveness measurement approach, difficulty to evaluate countermeasures can be quantified. Utilizing the improved optimization model allows for deriving an optimal investment portfolio for each countermeasure within a fixed budget, considering information security costs, quantities, and effectiveness. This aids in securing the information security budget and effectively addressing information security threats.

Understanding the Influence of Funder Characteristics on Information Processing and Pledging Intention on a Reward-based Crowdfunding Platform (보상기반 크라우드 펀딩 플랫폼에서 투자자의 특성이 정보 처리 및 투자 의사결정에 미치는 영향)

  • Ilyoo Barry Hong;KwangWook Gang;Hoon S. Cha
    • Information Systems Review
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    • v.25 no.4
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    • pp.265-290
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    • 2023
  • Even though crowdfunding has become popular as a novel means of raising capital for early-stage ventures and startups through an Internet-based platform, it is unclear how a funder's characteristics, such as motivation and ability, influence their information processing and pledging decision. This study aims to propose and test a research model for determining the relationships between a funder's personal attributes, information processing style, and funding intention. To test the research model, we collected data from 139 Amazon Mechanical Turk participants through an online questionnaire survey. The findings indicate that a funder's self-efficacy has a positive effect on heuristic processing but has no significant effect on systematic processing. By contrast, a funder's personal relevance positively influences both systematic and heuristic processing. Furthermore, heuristic processing, as well as perceived value and perceived risk, influence pledging intentions positively. Our findings potentially contribute to improving the design of crowdfunding platforms to better support a funder's information needs. Based on our findings, we discuss the implications of our study as well as the directions for future research.

Strategies for Managing Dementia Patients through Improving Oral Health and Occlusal Rehabilitation: A Review and Meta-analysis

  • Yeon-Hee Lee;Sung-Woo Lee;Hak Young Rhee;Min Kyu Sim;Su-Jin Jeong;Chang Won Won
    • Journal of Korean Dental Science
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    • v.16 no.2
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    • pp.128-148
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    • 2023
  • Dementia is an umbrella term that describes the loss of thinking, memory, attention, logical reasoning, and other mental abilities to the extent that it interferes with the activities of daily living. More than 50 million individuals worldwide live with dementia, which is expected to increase to 131 million by 2050. Recent research has shown that poor oral health increases the risk of dementia, while oral health declines with cognitive decline. In this narrative review, the literature was based on the "hypothesis" that dementia and oral health have a close relationship, and appropriate oral health and occlusal rehabilitation treatment can improve the quality of life of patients with dementia and prevent progression. We conducted a literature search in PubMed and Google Scholar databases, using the search terms "dementia," "major neurocognitive disorder," "dentition," "occlusion," "tooth loss," "dental prosthesis," "dental implant," and "occlusal rehabilitation" in the title field over the past 30 years. A total of 131 studies that scientifically addressed dementia, oral health, and/or oral rehabilitation were included. In a meta-analysis, the random effect model demonstrated significant tooth loss increasing the dementia risk 3.64-fold (pooled odds ratio=3.64, 95% confidence interval [2.50~5.32], P-value=0.0348). Tooth loss can be an important indicator of cognitive function decline. As the number of missing teeth increases, the risk of dementia increases. Loss of teeth can lead to a decrease in the ascending information to the brain and reduced masticatory ability, cerebral blood flow, and psychological atrophy. Oral microbiome dysbiosis and migration of key bacterial species to the brain can also cause dementia. Additionally, inflammation in the oral cavity affects the inflammatory response of the brain and the complete body. Conversely, proper oral hygiene management, the placement of dental implants or prostheses to replace lost teeth, and the restoration of masticatory function can inhibit symptom progression in patients with dementia. Therefore, improving oral health can prevent dementia progression and improve the quality of life of patients.

An Ecosystem Model and Content Research of the Satellite Information Utilization Business (위성정보 활용 사업의 생태계 모델과 콘텐츠 연구)

  • Seungkuk Baik ;Jinhwa Roh;Hyounjoo Shim;Xuanning Zhu
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1075-1084
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    • 2023
  • Satellite-derived data is collected by observing the Earth and is used in various fields such as national defense, natural disasters, location-based services, infrastructure, environment, energy, marine, and insurance. This study aims to present the virtuous cycle structure of the satellite information data industry and the business ecosystem model of the industry. As a research method, cases were collected and categorized from the following areas: literature, online, application, and content. The results show that the ecosystem model of the satellite information data industry provides an approach to content services in public and commercial areas, and develops various algorithmic technologies to facilitate content production and services at the level of complex general-purpose technologies. Second, in terms of content typology, satellite information data can be subdivided into monitoring content, urban space monitoring content, and satellite information content. Third, the consumption value of satellite content could be subdivided into informational value, environmental, social and governance (ESG) value, educational value, and content value. In order to expand the global content market, Korea will need to focus on creating an ecosystem for the satellite information industry and discovering differentiated content. It will also need to increase the popularization and accessibility of data to the general public and promote the Korean K-Satellite Information Data Industry ecosystem through government support, policy efforts, and policies such as establishing legal systems, increasing investment, and training human resources.

A Study on the Domain Discrimination Model of CSV Format Public Open Data

  • Ha-Na Jeong;Jae-Woong Kim;Young-Suk Chung
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.12
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    • pp.129-136
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    • 2023
  • The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

A study of the multicomponent therapeutic recreation function intervention strategy by analysis on the operating condition of the cognitive rehabilitation program in dementia care center

  • Moon-Sook Lee;Byung-Jun Cho;Jae-Sik Yang
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.12
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    • pp.155-166
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    • 2023
  • This study was conducted with 50 elderly people each (5) participating in the cognitive rehabilitation treatment program at the Dementia Care Center in D City to derive the development direction and contents of a multidimensional therapeutic recreation program and a revitalization plan through analysis of the current status and actual conditions of the cognitive rehabilitation program at the Dementia Care Center. aperture) was selected, and 9 people were selected as the subject of expert group opinion collection. The collected data was SPSS ver. Using the 18.0 statistical program, descriptive statistics and the importance and priority of each component were analyzed by hierarchical structure analysis. First, unlike the needs of users, the cognitive rehabilitation support programs currently being provided are not sufficient and require considerable experience. It was found to be low, and the areas for improvement were the expansion of care and protection facilities and the development of various programs to meet the needs of users. Second, the importance and priority of each component of therapeutic recreation were categorized into 6 major categories: exercise therapy , middle category (16 items) behavior-centered approach to exercise therapy, small category (47 items) strength and brain gymnastics, and silver health gymnastics were the highest. This result shows that a multidimensional program plan that considers the priorities of each area must be made when developing a therapeutic recreation program.

Mapping Burned Forests Using a k-Nearest Neighbors Classifier in Complex Land Cover (k-Nearest Neighbors 분류기를 이용한 복합 지표 산불피해 영역 탐지)

  • Lee, Hanna ;Yun, Konghyun;Kim, Gihong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.6
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    • pp.883-896
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    • 2023
  • As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

A Case Study on the Management of Food Allergy - Focusing on the case of Children's Foodsevice Operations in Eunpyeong-gu - (식품알레르기 관리방안에 관한 사례연구 - 은평구 어린이급식소 사례를 중심으로 -)

  • Joohee, Han;Hyeri Kim;Jieun Kim;Hailee Hwang;Hayan Hwang;Jiwon Kang;Eunseo Ju;Hyeyeong Hwang;Jinyoung Byun;Jieun Choi;Yujin Park;Jihyun Park;Jina Lee;Wansoo Hong
    • Journal of the FoodService Safety
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    • v.3 no.2
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    • pp.74-77
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    • 2022
  • As the prevalence of food allergies increases, related hazards also increase. Among the victims of accidents, children under the age of 10 accounted for a significant portion, raising the need for management of them. To ensure that children are aware of the risk of food allergy for safe meal service and to prevent problems such as malnutrition and poor growth in growing children, the current status of food allergy is surveyed for teachers and parents of children's catering centers in Eunpyeong-gu, and 1: 1 Specialized projects were carried out to provide customized counseling, educational support, alternative diets, and educational materials. As a result, it was found that the improvement of professionalism of faculty members and parents greatly helped to create an environment in which nutritious meals can be provided safely.

Impact Analysis of Abolition of Royalty on Non-fungible Tokens Market (로열티 폐지가 대체 불가능 토큰 시장에 미치는 영향분석)

  • Eun Mi Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.365-370
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    • 2023
  • Royalty contributed to the development of the non-fungible token (NFT) ecosystem as a reward system that pays a portion of the sales to the creator whenever transactions occur. This study quantitatively analyzes the impact of the abolition of royalties, which is being expanded by some NFT marketplaces, on the NFT market, and qualitatively analyzes the results of the impact. The analysis results are as follows. First, the number of NFT mints is decreasing by causing creators to leave the NFT market and reducing new entry. Second, major NFT projects have refused to trade with marketplaces that have abolished royalties, leading to a decrease in the number of transactions. Third, the abolition of royalties has undermined the motivation of NFT creators to continue to develop their projects, leading to a drop in NFT floor prices. This study is expected to contribute to reducing the current negative impact in the short term by suggesting how the NFT community provides incentives to owners who voluntarily pay royalties independently of the policy of the NFT marketplace. In addition, it suggests that in the long run, fundamental solutions to the problem of abolishing royalties require improvements in technology related to royalty payments, cooperation between NFT marketplaces and NFT creators, and institutional support related to royalties.